Spring Boot AI Applications - A Developer’s Guide

A comprehensive guide to building modern, AI-enhanced enterprise applications with Spring Boot, covering everything from fundamentals to production deployment.

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About This Guide

This book provides a practical, hands-on approach to building modern Spring Boot applications enhanced with AI capabilities. Inspired by the teaching style of technical masters and the comprehensive approach of academic textbooks, it covers both fundamental concepts and advanced enterprise patterns.

What You’ll Learn

  • Modern Spring Boot development with Java 21+ and Virtual Threads
  • Authentication and Authorization using Keycloak with multi-tenant support
  • AI Integration patterns for enterprise applications
  • Enterprise Integration with message queues, databases, and external services
  • Production Deployment strategies with containerization and monitoring

Who This Book Is For

  • Java developers wanting to integrate AI into their applications
  • Spring Boot developers modernizing legacy systems
  • Enterprise architects building scalable, AI-enhanced platforms
  • DevOps engineers deploying AI-powered microservices

Getting Started

Prerequisites

  • Java 21 or later
  • Spring Boot 3.2+
  • Docker and Docker Compose
  • Basic knowledge of Spring Boot and REST APIs

Quick Start

  1. Clone the repository 
    git clone https://github.com/kaushikk/spring-boot-ai-developers-guide.git
cd spring-boot-ai-developers-guide
  2. Start the development environment 
    docker-compose up -d

  3. Follow along with Chapter 1

    Begin with Modern Spring Boot with Virtual Threads to set up your development environment.

Book Structure

Part I: Foundations

These chapters establish the foundation for modern Spring Boot development with enterprise-grade authentication.

  • Chapter 1: Modern Spring Boot with Virtual Threads Learn how to leverage Java 21’s virtual threads for massive concurrency in Spring Boot applications.

  • Chapter 2: Authentication and Authorization with Keycloak Set up enterprise-grade authentication with Keycloak, including social login and multi-tenant support.

  • Chapter 3: Multi-Tenant Architecture Patterns Design scalable multi-tenant applications with proper data isolation and security.

  • Chapter 4: Local File Databases and Edge Computing Build applications that work offline and at the edge with embedded databases.

Part II: Enterprise Integration

Enterprise applications require robust integration patterns. These chapters cover message-driven architectures, database patterns, and API design.

  • Chapter 5: Message-Driven Architecture Implement asynchronous processing with RabbitMQ, Kafka, and Spring Integration.

  • Chapter 6: Database Integration Patterns Master database access patterns, transactions, and data migration strategies.

  • Chapter 7: REST and GraphQL APIs Design and implement robust APIs with proper versioning and documentation.

  • Chapter 8: Event-Driven Microservices Build reactive microservices that communicate through events.

Part III: AI Integration

Learn how to enhance your Spring Boot applications with AI capabilities using modern patterns and frameworks.

  • Chapter 9: Building MCP Servers for AI Create Model Context Protocol servers to enable AI integration with your applications.

  • Chapter 10: LLM Service Integration Integrate Large Language Models into your Spring Boot applications.

  • Chapter 11: Vector Databases and Embeddings Work with vector databases for semantic search and recommendation systems.

  • Chapter 12: AI Agent Patterns Implement AI agents that can interact with your application’s business logic.

Part IV: Production and Scale

Production deployment requires careful consideration of security, monitoring, and performance. These chapters prepare your applications for enterprise deployment.

  • Chapter 13: Containerization and Deployment Package and deploy your applications using Docker, Kubernetes, and cloud platforms.

  • Chapter 14: Security at Scale Implement comprehensive security measures for production environments.

  • Chapter 15: Monitoring and Observability Set up monitoring, logging, and alerting for your AI-enhanced applications.

  • Chapter 16: Performance and Optimization Optimize your applications for high throughput and low latency.

Part V: Complete Case Study

  • Chapter 17: Building an AI-Powered Platform Follow a complete case study building a real-world AI-enhanced application.

  • Chapter 18: Troubleshooting and Debugging Learn debugging techniques for complex, distributed AI systems.

Code Examples

All code examples are available in the examples/ directory, organized by chapter. Each example includes:

  • Complete, runnable code
  • Docker Compose configurations
  • Step-by-step setup instructions
  • Testing strategies

Contributing

This book is a living document. We welcome:

  • Corrections and improvements to existing content
  • New examples and use cases
  • Additional chapters covering emerging technologies
  • Translations to other languages

Please see our Contributing Guidelines for details.

License

This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 International License.

You are free to share and adapt this material for any purpose, including commercial use, as long as you provide attribution and distribute any derivatives under the same license.

Acknowledgments

This book draws inspiration from several excellent technical works:

  • The practical approach of Manning’s “in Action” series
  • The comprehensive teaching style of Andrew Tanenbaum’s textbooks
  • The modern Java practices advocated by Dan Vega and Josh Long
  • The enterprise patterns documented in various Spring guides

Special thanks to the Spring Boot, Keycloak, and broader Java communities for their continuous innovation and knowledge sharing.

Start your journey into modern, AI-enhanced Spring Boot development with Chapter 1: Modern Spring Boot with Virtual Threads.